The presently disclosed technology generally concerns acomputer-based platform for integrating data from multiple systems including (but not limited to) point of sale (POS) terminals, video systems, electronic article surveillance (EAS) systems, automatic teller machines (ATMs), gas pumps, alarm systems, radio frequency identification (RFID) detection systems, etc. The subject computer-based platform is configured to gather and correlate data (e.g., transactional data and/or video data), package such data into multiple discrete system “events”, and to provide various features for proactively identifying selected events as “exceptions”. Additional aspects of the computer-based platform may be utilized to provide signaled identification to a user of identified exceptions and other integrated system data.
The ability to integrate and characterize data from multiple electronic systems can provide advantageous utility for a variety of different applications. For example, in a retail environment, certain types or patterns of employee or customer behavior at the register can be closely associated with fraud, theft or insufficient training. These types of behaviors generally result in a monetary loss by the owner of the retail business. As such, data monitoring and characterization of register transactions may be useful for loss prevention applications. Furthermore, transaction information from a point of sale terminal, especially specific information regarding identification of tendered items, is invaluable data for merchandizing and marketing applications. Video data corresponding to such transactional information may be utilized to evaluate customer demographics for marketing applications. Video data may also be analyzed in a transactional environment for operations applications, for example, to monitor register line counts, customer traffic patterns, etc. or for training applications to ensure employees maintain accepted performance levels. Additional applications may involve the integration and characterization of video and/or event data as related to security, safety, and liability issues.
Analyzing integrated system data, especially in retail environments, and searching for such events as those that characterize questionable employee behavior is gaining popularity among large retail organizations but is typically not practiced by less sophisticated organizations. Many organizations outsource this analysis and refer to it as “Data Mining” or “Exception Reporting”. In-house or third party systems presently in place are somewhat cumbersome and inefficient. The process of collecting the data from a multitude of geographically diverse locations, analyzing the data according to rigid guidelines, producing a written report, and distributing the written report can take several days and be very expensive. Further, the distributed Exception Reports are not typically tied to video data captured by surveillance systems in the store, as will be discussed in greater detail below.
As the devices that perform data entry (cash registers, data terminals, optical character readers, radio frequency readers, magnetic media readers, gas pumps, ATMs, and many other like input devices. etc.) become more sophisticated, larger quantities of alphanumeric characters describing the transaction are generated. If video data is to be integrated with such transactional data, the increase in information makes it much more difficult to overlay transaction data on a composite video image, as is effected in some known video surveillance systems. Furthermore, the general increase in information available when integrating transactional and/or video information from disparate electronic systems results in the need for a more convenient, feasible and proactive solution to analyze such information without relying solely on user review of the vast amount of information.